In the realm of artificial intelligence, the importance of data cannot be overstated. According to Donatelli, good data leads to good AI, while bad data results in bad AI. Riverbed places a strong emphasis on data in its product updates, such as the Aternity Digital Experience Management (DEM) technology released in April, which focuses on enhancing endpoint application delivery. Data also played a crucial role in shaping the company’s network acceleration platform update in May.
Riverbed’s platform evolution revolves around the concept of handling observability data at scale. Rather than creating a centralized data lake to store massive amounts of information, Riverbed has developed a unique architecture known as the Riverbed Data Store. This innovative approach functions as an intelligent indexing system, allowing for efficient data management without the need to physically move large datasets. By adopting this architecture, Riverbed can bring AI to the data instead of moving data to centralized AI systems, resulting in improved performance and security in observability platforms.
The Riverbed Data Store serves as a centralized index of indexes, as described by Riverbed CTO Richard Tworek. This approach minimizes the need for extensive metadata storage, enabling AI algorithms to access detailed information dynamically as needed. By moving AI to the data, Riverbed addresses common challenges associated with traditional observability platforms, offering a more efficient and secure solution for managing data at scale.
